User:Prof McCarthy/Multivector

A multivector is the result of a product defined for elements in a vector space V. A vector space with a linear product operation between vectors is called an algebra, see for example matrix algebra and vector algebra. The algebra of multivectors is constructed using the wedge product ʌ and is related to the exterior algebra of differential forms.

The set of multivectors on a vector space V is graded by the number of basis vectors that form a basis multivector. A multivector that is the product of p basis vectors is called a rank p multivector, or a p-vector. The linear combination of basis p-vectors forms a vector space denoted as Λ^p(V). The maximum rank of a multivector is the dimension of the vector space V.

The product of a p-vector and a k-vector is a k+p-vector so the set of linear combinations of all multivectors on V is an associative algebra, which is closed with respect to the wedge product. This algebra, denoted by Λ(V), is called the exterior algebra of V.

Wedge product

The wedge product operation used to construct multivectors is linear, associative and alternating, which reflect the properties of the determinant. This means for vectors u, v and w in a vector space V and for scalars α, β, the wedge product has the properties,

• Linear: $\mathbf {u} \wedge (\alpha \mathbf {v} +\beta \mathbf {w} )=\alpha \mathbf {u} \wedge \mathbf {v} +\beta \mathbf {u} \wedge \mathbf {w} ;$
• Associative: $(\mathbf {u} \wedge \mathbf {v} )\wedge \mathbf {w} =\mathbf {u} \wedge (\mathbf {v} \wedge \mathbf {w} )=\mathbf {u} \wedge \mathbf {v} \wedge \mathbf {w} ;$
• Alternating: $\mathbf {u} \wedge \mathbf {v} =-\mathbf {v} \wedge \mathbf {u} ,\quad \mathbf {u} \wedge \mathbf {u} =0.$

The product of p vectors is called a rank p multivector, or a p-vector. The maximum rank of a multivector is the dimension of the vector space V.

The linearity of the wedge product allows a multivector to be defined as the linear combination of basis multivectors. There are (ⁿ_p) basis p-vectors in an n-dimensional vector space.

Area and volume

The p-vector obtained from the wedge product of p separate vectors in an n-dimensional space has components that define the projected (p-1)-volumes of the p-parallelopiped spanned by the vectors. The square root of the sum of the squares of these components defines the volume of the p-parallelopiped.

The following examples show that a bivector in two dimensions measures the area of a parallelogram, and the magnitude of a bivector in three dimensions also measures the area of a parallelogram. Similarly, a three-vector in three dimensions measures the volume of a parallelepiped.

It is easy to check that the magnitude of a three-vector in four dimensions measures the volume of the parallelepiped spanned by these vectors.

Multivectors in R²

Properties of multivectors can be seen by considering the two dimensional vector space V=R². Let the basis vectors be e₁ and e₂, so u and v are given by,

$\mathbf {u} =u_{1}\mathbf {e} _{1}+u_{2}\mathbf {e} _{2},\quad \mathbf {v} =v_{1}\mathbf {e} _{1}+v_{2}\mathbf {e} _{2},$

and the multivector uʌv, also called a bivector, is computed to be,

$\mathbf {u} \wedge \mathbf {v} ={\begin{vmatrix}u_{1}&v_{1}\\u_{2}&v_{2}\end{vmatrix}}\mathbf {e} _{1}\wedge \mathbf {e} _{2}.$

This shows that the magnitude of the bivector uʌv is the area of the parallelogram spanned by the vectors u and v. Notice that because V has dimension two the basis bivector e₁ʌe₂ is the only multivector in ΛV.

The relationship between the magnitude of a multivector and the area or volume spanned by the vectors is an important feature in all dimensions. Furthermore, the linear functional version of a multivector that computes this volume is known as a differential form.

Multivectors in R³

More features of multivectors can be seen by considering the three dimensional vector space V=R³. In this case, let the basis vectors be e₁, e₂, and e₃, so u, v and w are given by,

$\mathbf {u} =u_{1}\mathbf {e} _{1}+u_{2}\mathbf {e} _{2}+u_{3}\mathbf {e} _{3},\quad \mathbf {v} =v_{1}\mathbf {e} _{1}+v_{2}\mathbf {e} _{2}+v_{3}\mathbf {e} _{3},\quad \mathbf {w} =w_{1}\mathbf {e} _{1}+w_{2}\mathbf {e} _{2}+w_{3}\mathbf {e} _{3},$

and the bivector uʌv is computed to be,

$\mathbf {u} \wedge \mathbf {v} ={\begin{vmatrix}u_{2}&v_{2}\\u_{3}&v_{3}\end{vmatrix}}\mathbf {e} _{2}\wedge \mathbf {e} _{3}-{\begin{vmatrix}u_{1}&v_{1}\\u_{3}&v_{3}\end{vmatrix}}\mathbf {e} _{1}\wedge \mathbf {e} _{3}+{\begin{vmatrix}u_{1}&v_{1}\\u_{2}&v_{2}\end{vmatrix}}\mathbf {e} _{1}\wedge \mathbf {e} _{2}.$

The components of this bivector are the same as the components of the cross product. The magnitude of this bivector is the square root of the sum of the squares of its components.

This shows that the magnitude of the bivector uʌv is the area of the parallelogram spanned by the vectors u and v as it lies in the three-dimensional space V. The components of the bisector are the projected areas of the parallelogram on each of the three coordinate planes.

Notice that because V has dimension three, there is one basis three-vector in ΛV. Compute the three vector,

$\mathbf {u} \wedge \mathbf {v} \wedge \mathbf {w} ={\begin{vmatrix}u_{1}&v_{1}&w_{1}\\u_{2}&v_{2}&w_{2}\\u_{3}&v_{3}&w_{3}\end{vmatrix}}\mathbf {e} _{1}\wedge \mathbf {e} _{2}\wedge \mathbf {e} _{3}.$

This shows that the magnitude of the three-vector uʌvʌw is the volume of the parallelepiped spanned by the three vectors u, v and w.

In higher dimensional spaces, the component three-vectors are projections of the volume of a parallelepiped onto the coordinate three-spaces, and the magnitude of the three-vector is the volume of the parallelepiped as it sits in the higher dimensional space.

Grassmann coordinates

In this section, we consider multivectors on a projective space P ⁿ, which provide a convenient set of coordinates for lines, planes and hyperplanes that have properties similar to the homogeneous coordinates of points, called Grassmann coordinates.

Points in a real projective space P ⁿ are defined to be lines through the origin of the vector space Rⁿ⁺¹. For example, the projective plane P ² is the set of lines through the origin of R³. Thus, multivectors defined on Rⁿ⁺¹ can be viewed as multivectors on P ⁿ.

A convenient way to view a multivector on P ⁿ is to examine it in an affine component of P ⁿ, which is the intersection of the lines through the origin of Rⁿ⁺¹ with a selected hyperplane, such as H: x_n+1=1. Lines through the origin of R³ intersect the plane E:z=1 to define an affine version of the projective plane that only lacks the points z=0, called the points at infinity.

Multivectors on P ²

Points in the affine component E: z=1 of the projective plane have coordinates x=(x, y, 1). A linear combination of two points p=(p₁, p₁, 1) and q=(q₁, q₁, 1) defines a plane in R³ that intersects E in the line joining p and q. The multivector pʌq defines a parallelogram in R³ given by,

$\mathbf {p} \wedge \mathbf {q} =(p_{2}-q_{2})\mathbf {e} _{2}\wedge \mathbf {e} _{3}-(p_{1}-q_{1})\mathbf {e} _{1}\wedge \mathbf {e} _{3}+(p_{1}q_{2}-q_{1}p_{2})\mathbf {e} _{1}\wedge \mathbf {e} _{2}.$

Notice that substitution of αp + βq for p multiplies this multivector by a constant. Therefore, the components of pʌq are homogeneous coordinates for the plane through the origin of R³.

The set of points x=(x, y, 1) on the line through p and q is the intersection of the plane defined by pʌq with the plane E: z=1. These points satisfy xʌpʌq=0, that is,

$\mathbf {x} \wedge \mathbf {p} \wedge \mathbf {q} =(x\mathbf {e} _{1}+y\mathbf {e} _{2}+\mathbf {e} _{3})\wedge {\big (}(p_{2}-q_{2})\mathbf {e} _{2}\wedge \mathbf {e} _{3}-(p_{1}-q_{1})\mathbf {e} _{1}\wedge \mathbf {e} _{3}+(p_{1}q_{2}-q_{1}p_{2})\mathbf {e} _{1}\wedge \mathbf {e} _{2}{\big )}=0,$

which simplifies to the equation of a line,

$\lambda :x(p_{2}-q_{2})+y(p_{1}-q_{1})+(p_{1}q_{2}-q_{1}p_{2})=0.$

This equation is satisfied by the points x= αp + βq for real values of α and β.

The three components of pʌq define the line λ and are called the Grassmann coordinates of the line. Because three homogeneous coordinates define both a point and a line, the geometry of points is said to be dual to the geometry of lines in the projective plane. This is called the principle of duality.

Multivectors on P ³

Three dimensional projective space, P ³, consists of all lines through the origin of R⁴. Let the three dimensional hyperplane, H: w=1, be the affine component of projective space defined by the points x=(x, y, z, 1). The multivector pʌqʌr defines a parallelepiped in R⁴ given by,

$\mathbf {p} \wedge \mathbf {q} \wedge \mathbf {r} ={\begin{vmatrix}p_{2}&q_{2}&r_{2}\\p_{3}&q_{3}&r_{3}\\1&1&1\end{vmatrix}}\mathbf {e} _{2}\wedge \mathbf {e} _{3}\wedge \mathbf {e} _{4}-{\begin{vmatrix}p_{1}&q_{1}&r_{1}\\p_{3}&q_{3}&r_{3}\\1&1&1\end{vmatrix}}\mathbf {e} _{1}\wedge \mathbf {e} _{3}\wedge \mathbf {e} _{4}+{\begin{vmatrix}p_{1}&q_{1}&r_{1}\\p_{2}&q_{2}&r_{2}\\1&1&1\end{vmatrix}}\mathbf {e} _{1}\wedge \mathbf {e} _{2}\wedge \mathbf {e} _{4}-{\begin{vmatrix}p_{1}&q_{1}&r_{1}\\p_{2}&q_{2}&r_{2}\\p_{3}&q_{3}&r_{3}\end{vmatrix}}\mathbf {e} _{1}\wedge \mathbf {e} _{2}\wedge \mathbf {e} _{3}.$

Notice that substitution of αp + βq + γr for p multiplies this multivector by a constant. Therefore, the components of pʌqʌr are homogeneous coordinates for the 3-space through the origin of R³.

The set of points x=(x, y, z, 1) on the plane through p, q and r is the intersection of the 3-space defined by pʌqʌr with the hyperplane H: w=1. These points satisfy xʌpʌqʌr=0, that is,

$\mathbf {x} \wedge \mathbf {p} \wedge \mathbf {q} \wedge \mathbf {r} =(x\mathbf {e} _{1}+y\mathbf {e} _{2}+z\mathbf {e} _{3}+\mathbf {e} _{4})\wedge \mathbf {p} \wedge \mathbf {q} \wedge \mathbf {r} =0,$

which simplifies to the equation of a plane,

$\pi :x{\begin{vmatrix}p_{2}&q_{2}&r_{2}\\p_{3}&q_{3}&r_{3}\\1&1&1\end{vmatrix}}+y{\begin{vmatrix}p_{1}&q_{1}&r_{1}\\p_{3}&q_{3}&r_{3}\\1&1&1\end{vmatrix}}+z{\begin{vmatrix}p_{1}&q_{1}&r_{1}\\p_{2}&q_{2}&r_{2}\\1&1&1\end{vmatrix}}+{\begin{vmatrix}p_{1}&q_{1}&r_{1}\\p_{2}&q_{2}&r_{2}\\p_{3}&q_{3}&r_{3}\end{vmatrix}}=0.$

This equation is satisfied by points x = αp + βq + γr for real values of α, β and γ.

The four components of pʌqʌr that define the plane π are called the Grassmann coordinates of the plane. Because four homogeneous coordinates define both a point and a plane in projective space, the geometry of points is dual to the geometry of planes.

In projective space the line λ through two points p and q can be viewed as the intersection of the affine space H: w=1 with the plane x=αp + βq in R⁴. The multivector pʌq provides homogeneous coordinates for the line,

$\lambda :\mathbf {p} \wedge \mathbf {q} =(p_{1}\mathbf {e} _{1}+p_{2}\mathbf {e} _{2}+p_{3}\mathbf {e} _{3}+\mathbf {e} _{4})\wedge (q_{1}\mathbf {e} _{1}+q_{2}\mathbf {e} _{2}+q_{3}\mathbf {e} _{3}+\mathbf {e} _{4}),$

$\qquad ={\begin{vmatrix}p_{1}&q_{1}\\1&1\end{vmatrix}}\mathbf {e} _{1}\wedge \mathbf {e} _{4}+{\begin{vmatrix}p_{2}&q_{2}\\1&1\end{vmatrix}}\mathbf {e} _{2}\wedge \mathbf {e} _{4}+{\begin{vmatrix}p_{3}&q_{3}\\1&1\end{vmatrix}}\mathbf {e} _{3}\wedge \mathbf {e} _{4}+{\begin{vmatrix}p_{2}&q_{2}\\p_{3}&q_{3}\end{vmatrix}}\mathbf {e} _{2}\wedge \mathbf {e} _{3}+{\begin{vmatrix}p_{3}&q_{3}\\p_{1}&q_{1}\end{vmatrix}}\mathbf {e} _{3}\wedge \mathbf {e} _{1}+{\begin{vmatrix}p_{1}&q_{1}\\p_{2}&q_{2}\end{vmatrix}}\mathbf {e} _{1}\wedge \mathbf {e} _{2}.$

These are known as the Plucker coordinates of the line, though they are also an example of Grassmann coordinates.

A line μ in projective space can also be defined as the set of points x that form the intersection of two planes π and ρ defined by rank three multivectors, so the points x are the solutions to the linear equations,

$\mu :\mathbf {x} \wedge \pi =0,\mathbf {x} \wedge \rho =0.$

In order to obtain the Plucker coordinates of the line μ, map the multivectors π and ρ to their dual point coordinates using the Hodge star operator,

$\mathbf {e} _{1}=*\mathbf {e} _{2}\wedge \mathbf {e} _{3}\wedge \mathbf {e} _{4},-\mathbf {e} _{2}=*\mathbf {e} _{1}\wedge \mathbf {e} _{3}\wedge \mathbf {e} _{4},\mathbf {e} _{3}=*\mathbf {e} _{1}\wedge \mathbf {e} _{2}\wedge \mathbf {e} _{4},-\mathbf {e} _{4}=*\mathbf {e} _{1}\wedge \mathbf {e} _{2}\wedge \mathbf {e} _{3},$

then

$*\pi =\pi _{1}\mathbf {e} _{1}+\pi _{2}\mathbf {e} _{2}+\pi _{3}\mathbf {e} _{3}+\pi _{4}\mathbf {e} _{4},\qquad *\rho =\rho _{1}\mathbf {e} _{1}+\rho _{2}\mathbf {e} _{2}+\rho _{3}\mathbf {e} _{3}+\rho _{4}\mathbf {e} _{4}.$

So, the Plucker coordinates of the line μ are given by

$\mu :(*\pi )\wedge (*\rho )={\begin{vmatrix}\pi _{1}&\rho _{1}\\\pi _{4}&\rho _{4}\end{vmatrix}}\mathbf {e} _{1}\wedge \mathbf {e} _{4}+{\begin{vmatrix}\pi _{2}&\rho _{2}\\\pi _{4}&\rho _{4}\end{vmatrix}}\mathbf {e} _{2}\wedge \mathbf {e} _{4}+{\begin{vmatrix}\pi _{3}&\rho _{3}\\\pi _{4}&\rho _{4}\end{vmatrix}}\mathbf {e} _{3}\wedge \mathbf {e} _{4}+{\begin{vmatrix}\pi _{2}&\rho _{2}\\\pi _{3}&\rho _{3}\end{vmatrix}}\mathbf {e} _{2}\wedge \mathbf {e} _{3}+{\begin{vmatrix}\pi _{3}&\rho _{3}\\\pi _{1}&\rho _{1}\end{vmatrix}}\mathbf {e} _{3}\wedge \mathbf {e} _{1}+{\begin{vmatrix}\pi _{1}&\rho _{1}\\\pi _{2}&\rho _{2}\end{vmatrix}}\mathbf {e} _{1}\wedge \mathbf {e} _{2}.$

Because the six homogeneous coordinates of a line can be obtained from the join of two point or the intersection of two planes, the line is said to be self dual in projective space.

Clifford product

W. K. Clifford combined multivectors with an inner product or metric defined on the vector space in order to obtain a general construction for hypercomplex numbers that include the usual complex numbers and Hamilton's quaternions.

The Clifford product between two vectors u and v is a linear and associative like the wedge product, and has the additional property that the multivector uv is coupled to the inner product u·v by Clifford's relation,

$\mathbf {u} \mathbf {v} +\mathbf {v} \mathbf {u} =-2\mathbf {u} \cdot \mathbf {v} .$

Clifford's relation preserves the alternating property for the product of vectors that are perpendicular, such as the orthogonal unit vectors e_i, i=1, ..., n in Rⁿ,

$\mathbf {e} _{i}\mathbf {e} _{j}+\mathbf {e} _{j}\mathbf {e} _{i}=-2\mathbf {e} _{i}\cdot \mathbf {e} _{j}=0,$

therefore the basis vectors are alternating,

$\mathbf {e} _{i}\mathbf {e} _{j}=-\mathbf {e} _{j}\mathbf {e} _{i},\quad i\neq j=1,\ldots ,n.$

In contrast to the wedge product, the Clifford product of a vector with itself is no longer zero,

$\mathbf {e} _{i}\mathbf {e} _{i}+\mathbf {e} _{i}\mathbf {e} _{i}=-2\mathbf {e} _{i}\cdot \mathbf {e} _{i},$

which yields

$\mathbf {e} _{i}\mathbf {e} _{i}=-1,\quad i=1,\ldots ,n.$

The set of multivectors constructed using Clifford's product yields an associative algebra known as a Clifford algebra. Inner products with different properties can be used to construct different Clifford algebras.

Examples

Geometric interpretation for the exterior product of n vectors (u, v, w) to obtain an n-vector (parallelotope elements), where n = grade, for n = 1, 2, 3. The "circulations" show orientation.

• 0-vectors are scalars;
• 1-vectors are vectors;
• 2-vectors are bivectors;
• (n − 1)-vectors are pseudovectors;
• n-vectors are pseudoscalars.

In the presence of a volume form (such as given an inner product and an orientation), pseudovectors and pseudoscalars can be identified with vectors and scalars, which is routine in vector calculus, but without a volume form this cannot be done without a choice.

In the Algebra of physical space (the geometric algebra of Euclidean 3-space, used as a model of 3+1 spacetime), a sum of a scalar and a vector is called a paravector, and represents a point in spacetime (the vector the space, the scalar the time).

Bivectors

Main article: Bivector

A bivector is therefore an element of the antisymmetric tensor product of a tangent space with itself.

In geometric algebra, also, a bivector is a grade 2 element (a 2-vector) resulting from the wedge product of two vectors, and so it is geometrically an oriented area, in the same way a vector is an oriented line segment. If a and b are two vectors, the bivector a ∧ b has

• a norm which is its area, given by

$\Vert \mathbf {a} \wedge \mathbf {b} \Vert =\Vert \mathbf {a} \Vert \,\Vert \mathbf {b} \Vert \,\sin(\phi _{a,b})$

• a direction: the plane where that area lies on, i.e., the plane determined by a and b, as long as they are linearly independent;
• an orientation (out of two), determined by the order in which the originating vectors are multiplied.

Bivectors are connected to pseudovectors, and are used to represent rotations in geometric algebra.

As bivectors are elements of a vector space Λ²V (where V is a finite-dimensional vector space with $\dim V=n$), it makes sense to define an inner product on this vector space as follows. First, write any element F ∈ Λ²V in terms of a basis (e_i ∧ e_j)_{1 ≤ i < j ≤ n} of Λ²V as

$F=F^{ab}e_{a}\wedge e_{b}\quad (1\leq a<b\leq n)$

where the Einstein summation convention is being used.

Now define a map G : Λ²V × Λ²V → R by insisting that

$G(F,H):=\,G_{abcd}F^{ab}H^{cd}$

where $G_{abcd}$ are a set of numbers.

Geometric algebra

See also: Blade (geometry)

In geometric algebra, a multivector is defined to be the sum of different-grade k-blades, such as the summation of a scalar, a vector, and a 2-vector. A sum of only k-grade components is called a k-vector, or a homogeneous multivector.

The highest grade element in a space is called a pseudoscalar.

If a given element is homogeneous of a grade k, then it is a k-vector, but not necessarily a k-blade. Such an element is a k-blade when it can be expressed as the wedge product of k vectors. A geometric algebra generated by a 4-dimensional Euclidean vector space illustrates the point with an example: The sum of any two blades with one taken from the XY-plane and the other taken from the ZW-plane will form a 2-vector that is not a 2-blade. In a geometric algebra generated by a Euclidean vector space of dimension 2 or 3, all sums of 2-blades may be written as a single 2-blade.

Applications

Bivectors play many important roles in physics, for example, in the classification of electromagnetic fields.

See also

• Blade (geometry)
• Paravector